A practical approach to estimate the benefits of non-marginal mortality risk reductions using the Value of a Statistical Life

Diego S. Cardoso and Ricardo Dahis. (Under review)

VSL with large risk change

Abstract An oft-used approach to estimate the benefits of mortality reduction involves multiplying the value of a statistical life (VSL) by the expected decrease in fatalities. This simple procedure approximates the benefits of small changes in mortality but inaccurately characterizes the value of large risk changes because it holds constant the VSL–a marginal rate of substitution. Building on the theoretical framework of the VSL, we outline a practical approach to calculate the benefits of non-marginal mortality reductions. This readily applicable approach yields closed-form expressions that only require statistics broadly available for VSL-based calculations. Moreover, this method inherently satisfies standard economic constraints, thus ruling out extreme valuations that exceed one’s resources. We illustrate this approach using recent empirical estimates of the VSL to estimate the benefits of social distancing actions to combat COVID-19–non-pharmaceutical interventions that can lead to substantial reductions in mortality risk for vulnerable groups. Our results indicate that the constant VSL approach can substantially overestimate the benefits of large mortality risk reductions: for a group of over 70 countries, this approach overestimates the aggregate benefits of social distancing by 74% on average.